Structured Logging
Definition
Structured logging stores events in separate, machine-readable fields.
Structured logging captures events in machine-readable fields instead of exclusively as free text lines.
Simply explained
Like a form instead of a free note: time, affected service, and result get their own fields and can be specifically evaluated.
Why it matters in practice
The term contributes to secure, maintainable, and high-performance web applications as well as resilient technical decisions.
Example from business
An API logs time, severity, service, correlation ID, and result code as separate fields.
Limits and pitfalls
- Personal data or secrets in the log, inconsistent fields, and uncontrolled volumes create security and cost risks.
Origin & history
With distributed systems and centralized log analysis, formats like JSON and standardized telemetry schemas have become widespread.
Use in mid-sized companies
- Possible application: An API logs time, severity, service, correlation ID, and result code as separate fields.
Frequently asked questions
What does Structured Logging mean?
Structured logging captures events in machine-readable fields instead of exclusively as free text lines. What should one pay attention to? Personal data or secrets in the log, inconsistent fields, and uncontrolled volumes create security and cost risks.
Sources
- Logs Data Model · OpenTelemetry, Logs Data Model
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: